Science to Data Science

I took part in S2DS Virtual 2019 that concluded in November. Although I was a bit apprehensive about the virtual format before the start of the programme, I must say that I was rather pleased with my experience at the end of S2DS. The entire cohort is... Read More divided in to teams of 4 (or 3) at the beginning and given a real problem from one of their partner companies (depending on your preference) to solve. Each team is assigned a company mentor and a technical mentor from Pivigo.

A large part of the programme hinges on effective teamwork. The team members stay connected all the time through Slack, Zoom, Hangouts, Skype, etc. We also had daily scrums in the mornings that were very useful to take stock of the situation and plan for the day. I realised that for succeeding in these kind of projects, it is important that each team member plays to their strength. The problem statement given by our client was not really well-defined, which probably mimics a real-life scenario in a company. This is where the experience during your PhD will come in handy. After numerous brainstorming and pair-programming sessions, we came up with a finished product in 5 weeks that was presented to of the full cohort, the Pivigo team, and the company mentors.

The Pivigo team organises a few webinars during the first week on good coding practices, teamwork, etc. but there are no technical presentations or teaching involved. During the course of your project, you'll have regular meetings with the client to discuss progress, and the technical mentor is always ready to help if you get stuck really bad. Apart from that, around 3-4 panel debates were organised where a number of data scientists were invited to talk about their journey and career path. There was also a daily Q&A session where the full cohort used to discuss a topic related to AI/data science, led by one participant per day. You'lI get to learn not only about different interesting topics, but also about your fellow participants. Another nice touch was the one-to-one speed-networking sessions where you get to meet each of your fellow participants. Having said that, the peer-networking is one aspect where the on-site programme clearly wins over the virtual one. I must add that all the Pivigo staff members are very helpful, and they really try to ensure that each participant is having a good experience during these 5 weeks.

Please note that this is not a traditional 'bootcamp' where you are first taught a topic and then handed out a set of exercises to test your knowledge. This is for people who are already comfortable with coding (Python/R) and have basic understanding of statistics and machine learning concepts. The rest you have pick up on the go. S2DS adds to your CV the commercial experience as a data science consultant which makes you ready to hit the job market. Another important point is that S2DS is a full-time commitment, you need to spend at least 8 hours everyday working on your team project.

Regarding job assistance, it is too early for me to comment since I've just started applying for jobs. But you do get access to the huge S2DS alumni network and job advertisements that are announced in members-only Slack channels. There is an informative webinar conducted towards the end of the programme that helps you to structure your job search, starting from designing your resume to negotiating your salary.

Overall I'd recommend S2DS to anyone willing to transition from academia to industry as a data scientist. :)

Pros: worked on a real project for a company from day 1, got lots of coding experience, learnt some new teamwork and communication skills, got honest career advice and made connections with a large alumni network.
Cons: long hours, perhaps the course... Read More length could be slightly longer.

I took part in the S2DS Virtual Program in October 2019 while based in Germany. The application process consists of an online application on the Pivigo website, followed by an interview which tests basic technical knowledge as well as asking general motivational... Read More questions. About 3 weeks before the program we were given access to several program-specific videos covering things such as programming in Python and R, data visualisation and git. The videos are very clear and great to get started with any topic you are unfamiliar with. Also provided is a document suggesting additional learning resources as well as interview preparation materials.

On starting the program there are several introductory talks for the first two or three days; however, the majority of the program (which lasts 5 weeks) consists of working on a real data science project from start to finish with a client. My team was working on an interesting project with the UK Food Standards Agency (FSA). On assigning projects, individual preferences are taken into account. The virtual format of the program works extremely well and is of great benefit, especially with regards to changes in working habits in recent times. The majority of the teams made use of Slack, Github, Zoom and Trello for communication and team organisation. The team is generally left to its own devices; however, regular meetings are organised with a company mentor (in our case from the FSA) and technical mentors from Pivigo to keep the team on track. Another nice touch is regular individual meetings with a personal mentor at Pivigo, where additional more private matters can be discussed.

Aside from the project, virtual networking sessions as well as Q&A sessions are organised to get to know the whole cohort. These sessions are not only great for practicing networking skills but also make you realise that everybody is in the same situation. A series of panel debates are also organised regularly with data scientists from startups, corporations and former S2DS alumni. These are very informative and give a good overview of the breadth and depth of roles available in the world of data science as well as allowing you to ask any questions to the panel.

A very helpful careers presentation was also given towards the end of the program, which really made me think about changing my approach to the job search. Immediately following the program individual CV and Linked In profile reviews can be requested at any time. You are also given access to the whole Pivigo S2DS alumni network (over 600). This is useful not only for access to privately shared job roles, but also as a knowledge resource for any technical challenges faced later in your career.

At the end of the program final team presentations are given in the form of a webinar in additional to the requirement of a written report for the client. Not only was there a great sense of achievement on completing the program but a real sense of community with the cohort. The program was an extremely useful topic in a recent interview I had: here the journey of doing a project from start to finish offered by S2DS was key. The interviewers were also impressed by how so much was achieved in just the space of 5 weeks.

I can wholeheartedly recommend the program to anybody interested in a career in data science. I would emphasise that for an academic thinking of moving into industry (like me), the experience is invaluable even if you do not end up pursuing a pure data science role as a lot of the things learnt here are transferrable to many related technical roles.

Datascience is a perfect field for scientists who want to change career and transfer their STEM skills and knowhow to the IT & Data sector, but it is not always easy to find the right opportunity to kick off the transition from science to data science.... Read More The S2DS programme provides this opportunity and actually delivers more than expected: datascience projects with trading companies/institutions, team-based work, presentation coaching, MBA microcourse, best coding practices, career advice, job fair, networking opportunities and much more. If you are looking for a data science programme think S2DS, it ticks many boxes!

I was looking to gain some experience in Data Science and chose the S2DS programme as it offered good exposure to practical data science projects and provided the opportunity to develop the skills required to pursue a career in data science.

The programme... Read More is well structured and the mentors provide good support and help you through the difficult parts of the programme. Though there are no technical training or courses in data science, the mini-MBA helps in understanding the role of data scientists in commercial projects.

Overall, I had a very positive experience and good exposure to data science projects.

I was involved in several data science projects before starting the program. However, these projects were limited to academic settings, often resulting in publications and proof-of-concept prototypes. These prototypes were often abandoned after publishing... Read More results in a scientific journal and rarely made it to "real-life" settings.

S2DS gave me a good taste of a typical data science project in industry, covering requirement elicitation, model development and deployment. I had a chance to work with brilliant fellow data scientists supervised by skilled mentors, available whenever their help was needed. The 5 weeks spent in London were both intense and rewarding at the same time. The program exceeded my expectations and I am extremely satisfied with the outcomes!

This program is very good. It can add to professional and personal growth. I got a lot of job opportunities for him. Only problem ia the higg cost, since I live in Brazil and the currency conversion is very bad. I recommend Bootcamp to everyone. Very... Read More good.

My mentor was very good and knew a lot about data science. The only con about this course is how expensive it is. It is a good program but they use a lot of third party sources for their lessons that are free online. For example one of the lessons was... Read More taught entirely through Kahn academy videos which are free online.

I was already employed as a software developer when I enrolled in S2DS, I had a PhD in astrophysics and I really wanted to exploit my skills into a data science job but at that time I had no idea about what was a data science job, how to move properly... Read More into this field, how to present yourself to the market such that your experience could be considered valuable by recruiters.

S2DS helped me in all of this things. Moreover I found a lot of cool and talented people, friends who inspired me and teach me a lot. When you have to learn things on books or by yourself sometimes it can take years, but when you have the luck to make a real experince and find someone who can teach you with passion, this can boost your learning.

When I arrived at S2DS I had no claim, I knew it wasn't a magic and that I had to work hard, then we struggled a lot to finish our project in time, we suffered together, we put in it all our effort but finally we were rewarded and this is why I remember so pleasantly this bootcamp.

S2DS is a great bootcamp, aimed at people with PhDs who are looking to leave academia and move into a professional data science environment. The course is a 5 week, campus based bootcamp, with the first two weeks consisting of lectures and the last 3... Read More weeks spent on an industrial project with one of the partner companies. The emphasis of S2DS is really on building your data science network- spending time with other S2DSers, and meeting data science professionals. The team organise many social events including panel debates, mixers, keynote presentations, and various partner companies also hosted us for mixer evenings.

S2DS is a great way to get an overview of the field, the types of data science roles you can get into, and to get an introduction to the different types of companies you can work for and their key differences. There is a great CV preparation element to the course and job adverts are circulated during the course as well as in the alumni community once the course is finished.

The lectures at the start of the course give a brief overview of the different core elements of data science: Git, SQL, brief introductions to Python and R, and also less mainstream topics such as ethics and team work. We also had a two day mini-MBA which covered accounting, economics and business strategy. The lectures were not very technical and only gave brief introductions to these areas as a pointer in the right direction of what to scrub up on. I believe this is in contrast to other PhD bootcamps which have a stronger focus on, for example, specific statistical techniques in data science. The project comprises most of the time at S2DS and is a lot of fun. It's tough, stressful, but fantastic to work with real companies on real data and to generate something of value. You are put into teams to work on the project and are supported by an S2DS technical mentor as well as a company mentor throughout.

I would definitely recommend S2DS to anyone looking to transition into data science, although I would say it's best to get up to scratch on all technical skills before starting the course as these are not covered in detail on the course- it's more of a last push to get you across the line into industry. It is busy, hectic, you'll need a few recovery days once the course finishes, but 100% worth it!